In blog 2 of our data lakehouse blog series, we discussed how Perficient’s Healthy Lakehouse solution accelerates time and cost to value, and can help crack the code to success in delivering solutions.
Next, we’d like to share some real-life examples of projects and solutions we’ve executed with our clients. These charts show just a few of the use cases we’ve built for past provider, payer, and life sciences clients, to paint a picture of the actual analytics value we’ve delivered.
Now let’s take a more in-depth look at a few specific projects and solutions which Perficient has executed with our clients.
Home Health Success Story
One of the country’s largest home healthcare providers asked Perficient to assist them to define, architect, and implement a modern data & analytics solution. They wanted to become an operationally integrated, data-driven organization and realized they needed help getting there.
For some background, this client experienced significant growth through acquisition over the past few years, which left their data sprawled across many systems. This data sprawl required significant manual effort to create operational and financial performance dashboards across operating units. Creating these dashboards involved first locating and collecting the necessary data, then stitching it together within spreadsheets, and then manually creating the dashboard itself.
There was also a real risk of a HIPAA data incident occurring due to limited controls around PHI and PII data, given the data sprawl mentioned.
To meet the client’s needs, we began by discovering the current data & analytics capabilities and challenges across people, processes, and technologies, and worked to define a realistic future state vision, strategy, and plan to get there. This included:
First understanding and prioritizing the business and IT needs and challenges
Defining the platform and program architecture, AND selecting the cloud platform and tools,
And defining the program structure, project organization, and execution plan to implement the roadmap.
Once the architecture and plan were in place, the hard work of building the solution began.
This started with a technical proof of concept and an initial MVP which was brought to production, followed by a series of quarterly releases which added incremental value as the data and analytics capabilities grew.
The solution was a fully functional cloud-based data lakehouse and analytics solution that provided financial and operational performance analytics across operating units, and included analytics like:
A staff-hours & revenue dashboard
A Skilled vs Unskilled worker performance scorecard
and Billing trend-analysis visualizations
This solution eliminated the need to have 4 highly skilled analysts spend upward of 2 weeks per quarter collecting and correlating this information just to create these executive dashboards. These analysts can now focus on identifying ways to improve performance as opposed to wrangling data and performing swivel chair integration in excel.
As an additional benefit, combining the data from multiple operating companies has allowed the organization to enhance its data governance capabilities and program, and help ensure data is being managed and protected from a HIPAA and HiTrust compliance perspective.
Academic Medical Center Case Study
This was an academic medical center that was running into challenges to integrate large data sets securely and quickly to make the data usable and valuable to its providers and researchers.
They initially had a traditional, on-premises enterprise data warehouse to store and analyze data. But this solution was too costly and could not scale to meet their business needs. They were spending a ton of time and money just to produce basic reports and dashboards to draw the simplest of correlations among their patient populations.
So, they decided to invest in a secure and scalable cloud solution that would reduce maintenance costs, increase efficiency, and provide the data and analytics platform they needed to power their journey toward translational and personalized medicine.
The cloud solution ended up providing them with a robust, self-service platform for quickly analyzing complex data sets, compiling large data analytics, providing structured data visualization, and incorporating a data distribution environment.
More importantly, it got data into the hands of the data scientists who were performing the analysis and data modeling, and the clinicians who will ultimately be driving decisions for their patients.
We were able to:
Integrate 6 million patient records
Reduce operating costs by 50%, which helped free up funds for other vital program development
Reduce data query times by 97%, allowing for accelerated research, which in turn was able to get more evidenced-based care into action
Also, the scalable storage easily met the research and clinical demands of the organization.
Perficient + AWS
Perficient understands the complexities of the healthcare industry and the unique challenges healthcare organizations face. Our healthcare practice delivers strategic business and technology consulting insights that help our clients transform with today’s digital consumer experience demands. This strategic guidance is then transformed into pragmatic technology solutions that improve clinical, financial, and operational efficiency.
As an AWS partner, we have extensive experience with Big Data, data warehousing, business intelligence, and analytics, and work with our clients to transform data into timely and actionable insights using AWS services such as AWS Glue, Amazon Redshift, Amazon Quicksight, and Athena.
Perficient’s healthcare practice is dedicated to helping healthcare organizations leverage data and analytics to improve care quality, access, and delivery, and to better manage the costs associated with providing that care.
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